mvpa2.kernels.npΒΆ

Kernels for Gaussian Process Regression and Classification.

Functions

 `squared_euclidean_distance`(data1[, data2, ...]) Compute weighted euclidean distance matrix between two datasets.

Classes

 `ConditionalAttribute`([enabled]) Simple container intended to conditionally store the value `ConstantKernel`(\*args, \*\*kwargs) The constant kernel class. `EnsureFloat`() Ensure that an input (or several inputs) are of a data type ‘float’. `EnsureListOf`(dtype) Ensure that an input is a list of a particular data type `ExponentialKernel`(\*args, \*\*kwargs) The Exponential kernel class. `GeneralizedLinearKernel`(\*args, \*\*kwargs) The linear kernel class. `LinearKernel`(\*args, \*\*kwargs) Simple linear kernel: K(a,b) = a*b.T `Matern_3_2Kernel`([length_scale, sigma_f, ...]) The Matern kernel class for the case ni=3/2 or ni=5/2. `Matern_5_2Kernel`(\*\*kwargs) The Matern kernel class for the case ni=5/2. `NumpyKernel`(\*args, \*\*kwargs) A Kernel object with internal representation as a 2d numpy array `Parameter`(default[, constraints, ro, index, ...]) This class shall serve as a representation of a parameter. `PolyKernel`(\*args, \*\*kwargs) Polynomial kernel: K(a,b) = (gamma*a*b.T+coef0)**degree `RationalQuadraticKernel`([length_scale, ...]) The Rational Quadratic (RQ) kernel class. `RbfKernel`(\*args, \*\*kwargs) Radial basis function (aka Gausian, aka ) kernel `SquaredExponentialKernel`([length_scale, sigma_f]) The Squared Exponential kernel class.

Exceptions

 `ConditionalAttribute`([enabled]) Simple container intended to conditionally store the value `ConstantKernel`(\*args, \*\*kwargs) The constant kernel class. `EnsureFloat`() Ensure that an input (or several inputs) are of a data type ‘float’. `EnsureListOf`(dtype) Ensure that an input is a list of a particular data type `ExponentialKernel`(\*args, \*\*kwargs) The Exponential kernel class. `GeneralizedLinearKernel`(\*args, \*\*kwargs) The linear kernel class. `LinearKernel`(\*args, \*\*kwargs) Simple linear kernel: K(a,b) = a*b.T `Matern_3_2Kernel`([length_scale, sigma_f, ...]) The Matern kernel class for the case ni=3/2 or ni=5/2. `Matern_5_2Kernel`(\*\*kwargs) The Matern kernel class for the case ni=5/2. `NumpyKernel`(\*args, \*\*kwargs) A Kernel object with internal representation as a 2d numpy array `Parameter`(default[, constraints, ro, index, ...]) This class shall serve as a representation of a parameter. `PolyKernel`(\*args, \*\*kwargs) Polynomial kernel: K(a,b) = (gamma*a*b.T+coef0)**degree `RationalQuadraticKernel`([length_scale, ...]) The Rational Quadratic (RQ) kernel class. `RbfKernel`(\*args, \*\*kwargs) Radial basis function (aka Gausian, aka ) kernel `SquaredExponentialKernel`([length_scale, sigma_f]) The Squared Exponential kernel class.